193results about How to "Efficient acquisition" patented technology

The invention relates to a high-voltage cable intelligent inspection method and system based on multimode identification, and the method comprises the steps: deploying an intelligent identifier and cable monitoring equipment according to the equipment characteristics and environmental conditions in a high-voltage cable line; reading identification data of the intelligent identification through a double-frequency reading device, and collecting cable state monitoring data through a cable monitoring device; the information is uploaded to the Internet of Things cloud platform; carrying out fusion analysis on the received data in the cloud platform, evaluating the health condition of the cable in combination with a historical record and a fault recognition model, and generating an inspection result; and displaying the inspection result through the intelligent monitoring center, calculating the risk score of each device according to the identification data, the cable state monitoring data and the fault risk prediction result, and dynamically adjusting the optimal inspection route and the inspection frequency. Compared with the prior art, unique identification and multi-dimensional information storage of the cable and accessory equipment of the cable are achieved, and the fineness and comprehensiveness of cable operation state monitoring are improved.

The invention provides a myocardial infarction positioning method based on cross-modal knowledge fusion. The method comprises the following steps: acquiring a target 1D-VCG signal and constructing a 2D-VCG image data set; extracting spatial features, time sequence features and pseudo tags from the 2D-VCG signals and the 1D-VCG signals through a teacher model and a student model; aligning and transforming the spatial features and the time sequence features through a cross-modal generator; and cross-modal knowledge fusion and MI positioning are realized through a cross-modal generator. According to the method, through knowledge enhancement and student enhancement strategies, the accuracy of myocardial infarction positioning is improved, and the overall framework of cross-modal learning is optimized through the adaptive weight method; the method is realized in a knowledge distillation form, spatial features of 2D-VCG are successfully fused into 1D-VCG time sequence analysis, and the positioning accuracy of myocardial infarction is remarkably improved by combining cooperative work of a teacher model, a student model and a cross-modal generator.

The invention provides a semiconductor equipment data acquisition method and a semiconductor equipment data acquisition system supporting standardized communication transformation, which are used for realizing data acquisition and process control on different types of semiconductor equipment, formulating corresponding communication rules for equipment conforming to a communication standard, and converting an equipment communication protocol by a cluster system so as to match a standard interface. For equipment which does not completely meet the standard but can realize communication through programming, the trunking system directly acquires required data and converts the required data to meet the standard interface specification. For equipment without communication capability, data is acquired through an equipment interface by adopting an image recognition technology, data input and function operation are realized through simulating keyboard and mouse operation, and finally, protocol conversion from data to a standard interface is completed by a cluster equipment control system. And the equipment data is converted into a message data packet conforming to a standard semiconductor equipment communication interface, so that docking with a semiconductor equipment data analysis and process control system is realized, and the production efficiency and quality of the semiconductor equipment are improved.

The invention discloses a network resource optimization method for network slices, which comprises the following steps of: acquiring historical flow data, user behavior data and network topology information of each network slice from each network node in real time by utilizing a distributed data acquisition system, and performing data preprocessing on the historical flow data, the user behavior data and the network topology information to form a feature data set; inputting the feature data set into a prediction model constructed based on an attention mechanism and a mixed density network algorithm, optimizing the network weight through a gradient descent algorithm, and training the prediction model; inputting feature data of the current moment into the trained prediction model, and outputting prediction values of probability distribution of different network slices for future traffic demands; and formulating a resource pre-allocation strategy according to the predicted probability distribution of different network slices for future traffic demands, and dynamically optimizing and adjusting network resources. According to the invention, through accurate resource pre-allocation, network resources are utilized to the maximum extent, the operation cost is reduced, and the resource utilization efficiency is improved.

The invention discloses a joint beam forming optimization method for an RIS auxiliary low-altitude communication system. The problem of performance bottleneck caused by interaction of active beam forming and passive beam forming is solved by adopting a genetic algorithm based on a dynamic adaptive theory. Aiming at the limitation of a standard optimization method, a hybrid strategy of genetic algorithm optimization and a full-connection neural network is explored, and intelligent collaborative setting of system parameters is realized. Simulation results show that the hybrid algorithm not only simplifies the calculation process to obtain the optimal network parameters, but also effectively optimizes the system structure by dynamically adjusting the RIS reflection configuration. On the basis, the signal transmission quality is improved, interference is reduced, and it is guaranteed that the RIS-assisted low-altitude unmanned aerial vehicle intelligent communication system stably and efficiently operates in a complex wireless transmission environment.

The invention provides a method for characterizing the heterogeneity of a millimeter-level shale oil and gas reservoir. The method mainly solves the problem that the reliability and accuracy of a reservoir evaluation result of an existing volume sampling method are low. The method is characterized by comprising the following steps that S1, shale millimeter-level mineral components are recognized and drilled; s2, based on the obtained powdery sample, oil-containing and non-oil-containing tests are carried out; determining occurrence pore size distribution to carry out reservoir characterization through comparison before and after pumping; s3, on the basis of the obtained powdery sample, carrying out oiliness characterization on different lamina / layered components; and S4, carrying out millimeter-level shale oil reservoir heterogeneity characterization on the basis of the reservoir property and oiliness results of the different strata / layered components. According to the method provided by the invention, the identification precision of the shale formation / stratified structure can be enhanced, millimeter-level fine representation of lithology of different formation / strata is realized, and favorable support is provided for shale oil enrichment mechanism, sweet spot prediction and the like.

The invention relates to the technical field of wetland ecosystem degradation identification, in particular to a wetland ecosystem degradation identification method and system. According to the technical scheme, the method comprises the following steps that a comprehensive wetland biodiversity monitoring system is constructed, and multiple types of sensors and high-definition cameras are deployed in a wetland so as to obtain multi-source data related to wetland organisms and environments; preprocessing the obtained original data to enable the original data to be suitable for subsequent artificial intelligence analysis; and biological species identification and biological diversity evaluation are respectively carried out by using an image identification technology based on deep learning and a machine learning algorithm. According to the method, the foundation is laid for analysis by comprehensively and accurately collecting wetland biological and environmental multi-source data and an effective preprocessing method; according to the method, biological species are accurately identified, diversity parameters are evaluated, indexes are reasonably set, trends are reliably analyzed by using a moving average method, data are periodically updated, model parameters and structures are adjusted, wetland changes are self-adapted, and wetland ecology is effectively monitored and evaluated.

The invention discloses a pose estimation method, computer equipment and a storage medium. The method comprises the following steps: acquiring point cloud data of a current frame, and performing feature point extraction on the point cloud data to obtain at least two types of feature points; performing region division on the feature points of each category to obtain at least two categories of feature points corresponding to each region; clustering processing is carried out on the feature points, corresponding to the areas, of the categories to obtain centroid point sets corresponding to at least two categories; and performing pose estimation by using the centroid point sets corresponding to the at least two categories to obtain the current pose of the target equipment. According to the scheme, the accuracy of pose estimation can be improved.

The invention relates to the technical field of ultrasonic measurement, in particular to a heart parameter measuring method and system. According to the heart parameter measurement method, the position of the heart is acquired, and the probe is finely positioned according to the position of the heart, so that the probe can accurately and quickly find and acquire the ultrasonic image at the standard section of the heart; then capturing a target standard section in the ultrasonic image by adopting a pre-trained self-supervised deep learning model; and finally, carrying out key frame extraction on the 2D echocardiogram video so as to measure a heart structure in a key frame to obtain heart structure parameters, cutting out a region of interest in the Doppler echocardiogram, and carrying out segmentation processing on the region of interest to obtain functional parameters of the heart. By means of the mode, various parameters of the heart can be accurately and efficiently obtained, full automation is achieved in the whole process, and the accuracy and consistency of various parameter test results of the heart are guaranteed.

The invention provides a coal rock impact tendency testing and evaluating method based on a dynamic strain gauge, which comprises the following steps: pretreating a coal rock structure standard test piece, performing a uniaxial compression test on the coal rock structure standard test piece, and acquiring a preset index test result of the coal rock structure standard test piece; constructing a model for evaluating the impact tendency of the coal rock structure based on a BP neural network algorithm; and taking the preset index test result as input, and obtaining the impact tendency grade of the to-be-tested coal rock structure test piece by using a BP neural network-based coal rock structure test piece impact tendency evaluation model. The invention further provides a coal rock impact tendency testing and evaluating system based on the dynamic strain gauge. According to the method, the accuracy and reliability of the impact tendency of the coal and rock mass are improved, the precision of the evaluation result is ensured, and the evaluation result of the impact tendency of the coal and rock mass is obtained more conveniently and efficiently.

The invention discloses a power transmission line reconstruction method combined with multi-parallel-line laser, and belongs to the field of power transmission line modeling, and the method comprises the steps: determining a target power transmission line region, and carrying out the three-dimensional scanning of a multi-parallel-line laser scanner, and obtaining the point cloud data of the region; shooting a plurality of groups of binocular stereo images by using a binocular camera to obtain regional image data; establishing a registration coordinate system, and registering the point cloud and the image data to obtain an initial three-dimensional model of the power transmission line; constructing a key component set, and carrying out geometric recognition and segmentation on the models to obtain a plurality of key component models; and optimizing the plurality of key component models to obtain a plurality of optimized component models, and performing model optimization on the initial three-dimensional model of the power transmission line to obtain an accurate three-dimensional model of the power transmission line. The technical problems of low precision and poor efficiency of three-dimensional model reconstruction of the power transmission line in the prior art are solved, and the technical effects of improving the three-dimensional model reconstruction precision of the power transmission line and realizing efficient and accurate three-dimensional reconstruction of the power transmission line are achieved.

The invention provides biopsy liquid and application thereof in pig blastocyst laser cutting, and belongs to the technical field of animal biology. The invention provides a biopsy solution and a preparation method thereof, the biopsy solution can be applied to pig blastocyst biopsy by laser cutting, the problem that at present, no adaptive biopsy solution exists for laser cutting of pig blastocyst is solved, and the invention further provides a method for laser cutting of pig blastocyst by using the biopsy solution. The problems of embryo cell injury, embryo development potential damage and the like possibly caused by laser cutting of the pig blastocyst in the prior art are solved. The biopsy liquid and the use method thereof can be efficiently and accurately applied to acquisition of pig blastocyst trophoblast cells, and are low in cost and good in repeatability.

The invention discloses an image reconstruction algorithm, an image processing method and device, a vehicle and a storage medium. The image processing method comprises the steps of obtaining a visible light image and an auxiliary modal image to be fused; and performing fusion reconstruction on the visible light image and the auxiliary modal image by using an image reconstruction algorithm to obtain a target image, the image reconstruction algorithm comprising a step of completing a feature extraction task of the associated visible light image by using a high-frequency attention mechanism and a Fourier convolution mechanism in the high-frequency attention block. Therefore, the high-frequency information in the visible light image with various image qualities can be rapidly and effectively extracted through the image reconstruction algorithm, so that the target image is obtained by fusing and reconstructing the visible light image and the auxiliary modal image based on the effectively extracted high-frequency information; and features in a visible light image and features in an auxiliary modal image are clearer. Therefore, it can be ensured that images with high quality can be obtained when shooting is carried out in various shooting environments.

The invention belongs to the technical field of knowledge tracking, and particularly discloses a knowledge tracking method based on various learning behaviors. The knowledge tracking method based on various learning behaviors comprises three parts of data preprocessing and vector representation coding, a multi-head self-attention mechanism fusing a forgetting behavior and a transformation relation between the behaviors, and model training and prediction. According to the invention, on the basis of various learning behavior data, a knowledge tracking problem is modeled from a whole-process learning scene of a learner, so that a conversion relation of different types of learning behaviors and a personalized learning mode of the learner can be modeled by a built knowledge tracking model of various learning behaviors; and meanwhile, a learner forgetting behavior based on learning time and repetition frequency modeling is introduced, so that the knowledge state change condition in the whole learning process of the learner is better modeled, the knowledge state information of the learner is effectively acquired from various learning behaviors, and a knowledge tracking task is completed.

The invention relates to the field of robots, and discloses a cube carrying and angle and posture adjusting robot which comprises a movable chassis; the XZ-axis linear moving platform is arranged on the moving chassis so as to move in the X-axis direction and the Z-axis direction. The Y-axis linear moving assembly is arranged on the rear portion of the X-Z-axis linear moving platform and drives the cubic object to linearly move along the Y axis. The obtaining mechanisms are arranged on the two sides of the XZ-axis linear moving platform and used for obtaining the cubic objects and placing the cubic objects in the XZ-axis linear moving platform. The posture adjusting mechanisms are arranged on the two sides of the XZ-axis linear moving platform and used for adjusting the posture of an object entering the XZ-axis linear moving platform. And the placing mechanism is arranged on the Y-axis linear moving assembly and used for obtaining the articles subjected to posture adjustment through the posture adjusting mechanism, the Y-axis linear moving assembly drives the articles to move to the designated position, and the articles are released to the designated position through the placing mechanism. According to the invention, acquisition, angle and posture adjustment, transportation and stacking of the cube can be realized.

A hydraulic power plant water-collecting well and pool semi-supervised flooding detection method based on DINO constructs a semi-supervised target detection network through the steps of network construction, model construction and function optimization, and can realize high-quality detection of flooding detection tasks without performing complete manual annotation on unannotated images collected by a hydraulic power plant. The learning device is constructed by a target detection network DINO based on Transform, deep information contained in an image can be efficiently extracted by utilizing the strong long-range modeling capability of the learning device, and then object query with strong representation capability is generated. A cross-view-angle object query unification module designed based on a mean square error obtains effective features with an invariable extraction view angle by aligning the features extracted after executing different image enhancement operations on the same image, and enhances the generalization ability of the model to a flood detection task.

The invention discloses a data processing method and device, a storage medium and electronic equipment. The method comprises the following steps: acquiring multi-source business data sent by different business systems by using a target intelligent model; using the target intelligent model to determine a target knowledge graph according to the multi-source business data; in response to the service request, using the target intelligent model to call an intelligent tool library to determine portrait data and service evaluation data associated with the target object, the intelligent tool library comprising a plurality of intelligent tools, different intelligent tools adopting a unified call interface, and each object comprising the target object; and executing the target task based on the portrait data and the business evaluation data by using the target intelligent model. The technical problems of slow data processing flow and low efficiency caused by complex interaction between business systems are solved.

The invention provides a semantic segmentation method, system and device and a storage medium. The semantic segmentation method comprises the following steps: respectively extracting voxel features and image features based on initial point cloud data and image data of a target scene; obtaining a first point-by-point feature and a second point-by-point feature according to the voxel feature and the image feature so as to further obtain a geometric fusion feature and a semantic fusion feature; modeling according to the geometric fusion features and the semantic fusion features to obtain a semantic segmentation model; and inputting to-be-segmented target point cloud data into the semantic segmentation model so as to perform semantic segmentation on a target scene. According to the invention, the continuity and integrity of the features are improved; and spatial structure information can be reserved, the semantic understanding depth is enhanced, and global context features can be captured.

The invention belongs to the field of environmental noise seismic exploration, and particularly relates to a virtual source record automatic selection method suitable for environmental noise seismic exploration, which comprises the following steps: step 1, preprocessing original environmental noise seismic data to obtain preprocessed environmental noise seismic data; step 2, reconstructing virtual source seismic records of different time periods at each receiving point position by using the preprocessed environmental noise seismic data; 3, linear scanning superposition calculation processing is carried out on the positive time half axis and the negative time half axis of each section of virtual source seismic record, and scanning superposition amplitude curves based on different linear speeds are obtained; comparing and analyzing the maximum amplitude value of the scanning and superposition amplitude curve based on the positive and negative time half-axis virtual source seismic record, and automatically selecting the virtual source seismic record; and step 4, repeating the step 3, and realizing automatic selection of the virtual source seismic records at different time periods at each receiving point position. According to the invention, automatic screening of high-quality virtual source seismic records rich in surface wave information can be realized.

The invention relates to an information display method and device, electronic equipment, a storage medium and a program product. The method comprises the following steps: in response to a target account, triggering an acquisition instruction for a target object, and displaying a resource transfer aggregation option which is an option for aggregating multiple non-instant resource transfer channels, the resource transfer aggregation option refers to a mode of executing resource transfer by using any aggregated non-instant resource transfer channel after the target account confirms that the target object is acquired; and under the condition that the resource transfer aggregation option is selected and object acquisition continues to be executed, displaying object acquisition success prompt information of the target object. According to the technical scheme provided by the invention, the display resources of the object acquisition page can be saved, the user object acquisition decision cost can be reduced, and the non-instant resource transfer mode can be flexible and controllable.

The utility model discloses a breast pumping assembly and a breast pump. The breast pumping assembly is applied to the breast pump and comprises a milk storage container, a milk guide part and a sealing part. The milk storage container comprises a container main body and a container cover plate, the container cover plate covers and seals the container main body, and a milk storage cavity is defined by the container cover plate and the container main body; the milk guide piece is connected to the side, facing the milk storage cavity, of the container cover plate or connected to a fixing piece of the breast pump, penetrates through the container cover plate and extends into the milk storage cavity, and the milk guide piece is provided with a milk guide channel; wherein the container cover plate is provided with a milk pouring opening communicated with the milk storage cavity, and the milk pouring opening is detachably sealed by the sealing piece. According to the breast pumping assembly, the situation that the sealing piece shields the sight line of a user for checking the breast guiding channel is avoided, the user can rapidly and effectively obtain the problems existing in the using process of the breast pump, and the using experience feeling of the user is improved.

A head-removed shrimp posture detection method based on machine vision comprises the following steps: carrying out three-channel separation on a head-removed shrimp image in an HSV space, and selecting an optimal channel according to a foreground and background difference to obtain a head-removed shrimp binary image; obtaining three distance transformation heat maps of the binarized image of the head-removed shrimp, and selecting an optimal heat map according to the extraction matching degree of the central area of the shrimp head to obtain a central area image of the shrimp head; performing corner detection on the prawn head center area image, and fitting corner coordinates through a straight line to obtain a prawn head and prawn back orientation datum line; comparing the distances between the two wide sides of the minimum enclosing rectangle of the binarized image of the head-removed shrimp and the two end points of the shrimp head orientation datum line to obtain a shrimp head orientation vector; comparing the distance between the long side, tightly attached to the shrimp back, in the minimum bounding rectangle of the binarized image of the head-removed shrimp and the two end points of the shrimp back orientation datum line to obtain a shrimp back orientation vector; and the orientation vectors of the shrimp head and the shrimp back represent the attitude information of the head-removed shrimp. The method can accurately and stably detect the postures of the head-removed shrimps at low cost, and belongs to the shrimp posture image processing technology.

The invention discloses a method for generating a medium-voltage topological graph of a distribution network based on line crossing regularity. The method belongs to the technical field of topological graph generation, and comprises the following steps: obtaining power distribution network line equipment data, and preprocessing the power distribution network line equipment data to obtain a graph construction preliminary data packet; constructing an original topological graph according to the graph construction preliminary data packet, and performing regular arrangement processing on the original topological graph to obtain a preliminary regular topological graph; performing cross regularization processing on the preliminary regularized topological graph to obtain a regularized topological graph; and performing color rendering on the normalized topological graph to obtain a final distribution network medium-voltage topological graph. The beautiful and clear medium-voltage topological graph meeting the operation management requirements of the distribution network is automatically and efficiently generated, and the working efficiency of services such as distribution network planning, scheduling and line loss treatment is improved.

The invention provides an attention-fused remote sensing image road information extraction method and device, and the method comprises the steps: obtaining an original remote sensing image, carrying out the multi-scale feature extraction and global pooling of the original remote sensing image, obtaining the multi-scale local features and global pooling features, and carrying out the global pooling of the multi-scale local features and the global pooling features; fusing the multi-scale local features and the global pooling features by adopting an attention mechanism module to form shallow attention fusion features; different weights are given to the shallow attention fusion features, layered dynamic weighted stacking is carried out, deep attention fusion features in a dynamic weighted stacking result are extracted by using a convolution attention module, and the shallow attention fusion features and the deep attention fusion features are subjected to jump connection to obtain remote sensing image road information. Wherein the convolution attention module calculates a dynamic weighted combination loss value by using a BCE loss value and a Dice loss value, and adjusts model parameters based on the dynamic weighted combination loss value. According to the scheme, the feature information extraction efficiency and extraction precision are improved.

The invention provides a tumor diagnosis and treatment standardized quality control method and system based on a domain-specific language. The method comprises the following steps: acquiring professional tumor quality control indexes; the semantics of the index is recognized, a semantic logic relation is determined based on the semantics, index input data needed by the index are calculated, and the semantic logic relation indicates a relational expression describing a quality control index result determined based on the index input data; an index calculation task is generated based on the semantic logic relationship, a task is selected from a plurality of predefined tasks set according to a predetermined medical rule based on the index input data so as to generate an index composite task, the task logic of the index composite task is a directed acyclic graph, and a final node of the directed acyclic graph is the index calculation task, the plurality of predefined tasks and the index calculation task are described by a specific language in the tumor field; and inputting the medical data into the index composite task to obtain a tumor professional quality control index result.

The invention discloses a water-air fast scanner and a water bottom scanning method based on the water-air fast scanner, and relates to the field of water body ecological environment investigation. The problems that an existing underwater scanner cannot be suitable for a shallow water area with the water depth smaller than 5 m, GPS position information and a real scanning position are staggered, and the position precision of a bottom map is reduced are solved. The method comprises the following steps: determining a deployment mode of a water-air rapid scanner, and selecting a corresponding baseline length and array spacing; configuring a working mode of the camera array, and synchronizing the camera array and a GPS module clock; the water-air fast scanner records water bottom image information; extracting a video frame; calculating scanning track coordinate data of each camera; interpolation is carried out on the scanning track coordinate data, and a smooth GPS motion track is obtained; acquiring a route track of the camera according to the GPS motion track and the array spacing; and performing reconstruction processing on the route trajectory by adopting SfM to obtain a water bottom image. The method is suitable for the fields of ocean research, geological survey, underwater archaeological and the like.

The invention discloses a video content processing method and device, a server and a storage medium, and the method comprises the steps: obtaining an input target video, and carrying out the extraction of a target video frame and video text information according to the target video; obtaining visual features of the target video frame, constructing an abstract generation prompt text according to the visual features of the target video frame and the video text information, and inputting the abstract generation prompt text into a visual language model for abstract extraction to obtain a video abstract; acquiring a predefined attribute extraction prompt text, and inputting the attribute extraction prompt text and the target video frame into a visual language model to perform attribute extraction on the target video frame to obtain first video attribute information of the target video frame; and inputting the video abstract and the first video attribute information into a large language model to generate second video attribute information of the target video, thereby realizing extraction of video attributes.

The invention relates to the technical field of surgical navigation, and discloses a neurosurgical navigation acceleration processing method and system. According to the method, three-dimensional reconstruction is carried out by adopting an SART algorithm, a historical and real-time three-dimensional basic model is obtained, and a deep learning module constructed by a U-Net image segmentation network, a YOLO target detection network and a graph neural network is utilized to obtain an organizational structure and a surgical instrument position in real time and carry out path planning. Meanwhile, the data preprocessing module is used for conducting denoising and contrast enhancement processing on the real-time operation image data, and the image definition is improved. According to the method and the system, the precision, the real-time performance and the safety of the neurosurgery operation can be remarkably improved, and the method and the system have important clinical application value.

The invention provides a reservoir inherent frequency downhole in-situ measurement method based on neural network filtering. The method comprises the steps that (1) pulse shock waves are generated through a continuous high-voltage pulse discharging device to induce reservoir rock mass vibration; (2) acquiring natural vibration noise signal data of the continuous high-voltage pulse discharge device during pulse discharge at the wellhead; (3) acquiring a background noise signal of the continuous high-voltage pulse discharge device in a static state in a shaft and feedback vibration signal data during pulse discharge; (4) filtering and noise reduction are carried out on the high-noise background data; (5) carrying out vibration signal analysis; (6) obtaining a Hilbert marginal spectrum, and determining a correlation coefficient between each intrinsic mode and an original vibration signal; and (7) determining the inherent frequency of the target reservoir. According to the method, the inherent frequency measurement of the target reservoir can be directly carried out underground, the problem that the underground inherent frequency measurement is difficult or the indoor inherent frequency test is inaccurate is effectively solved, and the underground in-situ efficient acquisition of the inherent frequency of the reservoir is realized.

The invention discloses a multi-enzyme preparation for industrial cell dissociation as well as a use method and application thereof, and belongs to the technical field of extraction of seed cells for industrial culture of meat. According to the invention, a multi-enzyme preparation composed of a component 1 and a component 2 is adopted; the component 1 comprises neutral protease, hyaluronidase and elastase; and the component 2 comprises matrix metalloproteinase, papain and plasmin. The invention also discloses a preparation method and application of the multienzyme preparation. The reasonable enzyme ratio and the optimized treatment conditions are beneficial to protecting the integrity of cell membranes, maintaining high cell activity and remarkably improving the dissociation efficiency and the cell recovery amount; the complex enzyme preparation is high in adaptability, can be used for various tissue types and dissociation requirements, and is convenient for standardized and large-scale production; in combination with automatic dissociation equipment, the compound enzyme preparation can realize efficient and stable industrial operation, and provides important technical support and wide application prospects for the fields of meat culture industry, tissue engineering, cell therapy and the like.